The problem of divergence between stored and “live” biometric profiles has been known for some time. In known biometric verification systems, an individual's biometric signature is typically updated or refreshed after a verified contact with that individual. For example, U.S. Pat. No. 8,417,525 discusses a technique that stores several biometric patterns for a given individual to allow for effective averaging of variance tolerance over time and effective discards of erroneous prints. U.S. Pat. No. 6,519,561 discusses another example of a model adaptation system that can adapt models to track aging of a user's voice. U.S. Patent Application Publication No. 2004/0122669 also discusses a particular technique for adapting reference templates with a weighted interpolation of the stored data and corresponding data from a test utterance.
However, in such known systems, it is difficult to effectively exclude fraudsters from affecting the effectiveness of this mechanism. Moreover, the effectiveness and robustness of the system deteriorates where an individual does not make regular contact with the system, resulting in undesirable false rejections due to biometric drifting beyond the predefined expected system thresholds.
What is desired is an improved system and method for biometric verification with adaptable models that enables effectiveness and robustness for all users irregardless of the frequency of engagement with the verification system.